Python: Automate the Boring Stuff Training Course

This instructor-led, live training in US (online or onsite) is designed for data scientists and software engineers who wish to utilize Dask within the Python ecosystem to build, scale, and analyze large datasets for government. By the end of this training, participants will be able to: - Set up the necessary environment to begin building big data processing systems using Dask and Python. - Explore the features, libraries, tools, and APIs available in Dask. - Understand how Dask enhances parallel computing capabilities in Python. - Learn techniques for scaling the Python ecosystem (including Numpy, SciPy, and Pandas) using Dask. - Optimize the Dask environment to ensure high performance when handling large datasets.

This instructor-led, live training in US (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy for government applications.

By the end of this training, participants will be able to:

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy for government workflows.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code to ensure compliance with public sector governance standards.

This instructor-led, live training (available online or on-site) is designed for developers who aim to utilize the FARM (FastAPI, React, and MongoDB) stack to create dynamic, high-performance, and scalable web applications for government use. By the end of this training, participants will be able to: - Set up a development environment that seamlessly integrates FastAPI, React, and MongoDB. - Understand the fundamental concepts, features, and benefits of the FARM stack. - Learn how to develop REST APIs using FastAPI. - Gain proficiency in designing interactive applications with React. - Develop, test, and deploy both front-end and back-end components of applications using the FARM stack.

This instructor-led, live training (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly for government projects. By the end of this training, participants will be able to: - Set up the necessary development environment to create APIs using Python and FastAPI. - Develop APIs more quickly and easily leveraging the FastAPI library. - Understand how to create data models and schemas based on Pydantic and OpenAPI standards. - Integrate APIs with a database using SQLAlchemy. - Implement security and authentication in APIs utilizing FastAPI tools. - Build container images and deploy web APIs to a cloud server for government use.

The objective of this course is to provide a foundational proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on numerous practical examples, this course teaches participants how to utilize the most essential components of Machine Learning, make informed data modeling decisions, interpret algorithm outputs, and validate results.

Our goal is to equip you with the skills necessary to confidently understand and use the core tools from the Machine Learning toolbox, while avoiding common pitfalls in Data Science applications. This course is designed to enhance your capabilities for government workflows, ensuring alignment with public sector governance and accountability standards.

The objective of this course is to enhance proficiency in applying Machine Learning methods in practical scenarios. Utilizing the Python programming language and its various libraries, and through a wide range of practical examples, this course instructs participants on how to effectively use key Machine Learning components, make informed data modeling decisions, interpret algorithm outputs, and validate results.

Our goal is to equip you with the skills necessary to confidently understand and utilize the essential tools from the Machine Learning toolbox, while avoiding common pitfalls in Data Science applications for government.

This instructor-led, live training in US (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis. By the end of this training, participants will be able to: - Set up the necessary environment to start developing Pandas workflows at scale with Modin. - Understand the features, architecture, and advantages of Modin for government applications. - Differentiate between Modin, Dask, and Ray in terms of their suitability for various data processing tasks. - Perform Pandas operations more efficiently using Modin. - Implement the entire Pandas API and functions to enhance data analysis capabilities.

In this instructor-led, live training in US, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies relevant to public sector workflows and governance will be examined, and the concepts will be applied to hands-on lab projects for generating content tailored for government.

By the end of this training, participants will be able to:

• Utilize NLG to automatically generate content for various industries, including journalism, real estate, weather reporting, and sports, with a focus on applications for government.
• Select and organize source content, plan sentences, and prepare a system for the automatic generation of original content that aligns with public sector needs.
• Understand the NLG pipeline and apply the appropriate techniques at each stage to ensure compliance with governmental standards.
• Comprehend the architecture of a Natural Language Generation (NLG) system designed for government use.
• Implement the most suitable algorithms and models for analysis and ordering, ensuring they meet the requirements of public sector workflows.
• Pull data from publicly available data sources as well as curated databases to use as material for generated text that supports government operations.
• Replace manual and laborious writing processes with computer-generated, automated content creation that enhances efficiency and accountability in government tasks.

In this instructor-led, live training for government participants in [location], attendees will gain proficiency in the most relevant and cutting-edge machine learning techniques using Python. Through hands-on exercises, they will develop a series of demo applications involving image, music, text, and financial data. By the end of this training, participants will be able to: - Implement machine learning algorithms and techniques for solving complex problems. - Apply deep learning and semi-supervised learning methods to applications involving image, music, text, and financial data. - Optimize Python algorithms to their maximum potential. - Utilize libraries and packages such as NumPy and Theano.

Python is a high-level programming language renowned for its clarity and readability.

In this instructor-led, live training, participants will learn how to apply Python in the context of quantitative finance.

By the end of this training, participants will be able to:

• Comprehend the foundational principles of Python programming
• Leverage Python for financial applications, including the implementation of mathematical techniques, stochastic models, and statistical methods
• Develop financial algorithms using optimized Python code

Audience

• Software developers
• Quantitative analysts

Format of the course

• A combination of lectures, discussions, exercises, and extensive hands-on practice tailored for government professionals

Python is a programming language that has gained significant popularity in the financial sector. Adopted by major investment banks and hedge funds, it is used to develop a wide array of financial applications, from core trading systems to risk management platforms.

In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a variety of finance-related challenges.

By the end of this training, participants will be able to:

• Understand the fundamentals of the Python programming language
• Download, install, and maintain the best development tools for creating financial applications in Python
• Select and utilize the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
• Build applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• This training is designed to provide solutions for some of the primary challenges faced by finance professionals. If you have a specific topic, tool, or technique that you would like to cover or expand upon, please contact us to arrange.

Govtra offers this course for government personnel and organizations looking to enhance their financial technology capabilities and align with public sector workflows, governance, and accountability standards.

This instructor-led, live training in US (online or onsite) is designed for government developers who wish to enhance their skills in advanced Python programming techniques. The course covers the application of this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, user interface programming, and maintenance scripting, all tailored to meet the specific needs for government workflows and governance.

This course is designed for individuals seeking to learn the Python programming language, with a focus on both the core language and its libraries. It highlights the most valuable and relevant libraries developed by the Python community. Python is widely used in various sectors, including business and scientific research, making it one of the most popular programming languages. The course can be delivered using the latest version of Python 3.x, incorporating practical exercises that leverage its full capabilities. These exercises are compatible with a variety of operating systems, including all versions of UNIX, Linux, Mac OS X, and Microsoft Windows. Approximately 70% of the course time is dedicated to hands-on practical exercises, while 30% is allocated for demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the course. Note: The training can be customized to meet specific needs upon prior request ahead of the proposed course date, ensuring it aligns effectively with the requirements for government use.

Selenium is an open-source framework designed for automating web application testing across various browsers. Selenium 4 introduces enhanced WebDriver APIs, native relative locators, and improved grid support. Python, with its simplicity and robust integration with testing frameworks such as Pytest, is a powerful choice for developing scalable and maintainable test automation suites. This instructor-led, live training (online or onsite) is aimed at beginner to intermediate testers and developers who wish to use Selenium with Python to automate web application testing in real-world environments for government projects. By the end of this training, participants will be able to: - Install and configure Selenium with Python in a test environment. - Build robust test automation scripts using Selenium WebDriver and Pytest. - Apply the Page Object Model (POM) for maintainable test frameworks. - Run tests across multiple browsers using Selenium Grid. - Integrate automated tests with CI/CD pipelines. - Troubleshoot common issues and apply best practices for automation stability. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

In Python Machine Learning, the Text Summarization feature can process input text to generate a concise summary. This functionality is accessible both from the command line and as a Python API/library. One significant application for government is the rapid creation of executive summaries, which is particularly useful for organizations that need to review large volumes of text data before generating reports and presentations. This instructor-led, live training will guide participants in using Python to develop a simple application that automatically generates a summary of input text. By the end of this training, participants will be able to: - Utilize a command-line tool for summarizing text. - Design and implement Text Summarization code using Python libraries. - Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17. **Audience** - Developers - Data Scientists **Format of the Course** - Part lecture, part discussion, exercises, and extensive hands-on practice